基于序贯平差的长距离基准站间模糊度快速固定
Fast Ambiguity Resolution Between Long-Range Base Stations Based on Sequential Adjustment
-
摘要: 序贯平差方法是长距离网络RTK基准站间模糊度固定中的常用方法,该方法充分利用了卫星间的相关信息以及多余观测量,是理论严密且十分有效的方法。一般文献中只给出了参数不变的序贯平差公式。但是,观测过程中的参数是不断变化的,参数不变的序贯平差公式并不适用于网络RTK系统。此外,对于序贯平差而言,由于一般不存储历史观测值,因此,模糊度固定后无法将其带入原观测方程重新平差,这导致法方程更新困难。针对以上问题,本文给出了参数变化的序贯平差公式及严密的推导过程,并给出了模糊度固定后法方程的更新方法。结合长距离网络RTK基准站间模糊度固定问题,通过实验,证明了给出的序贯平差公式和法方程更新方法正确有效。Abstract: Sequential adjustment is commonly used for base station ambiguity resolution in long-range Network RTK.It is a very effective method with a strict theory that takes fully into account the correlation information between satellites as well as redundant observations. In previous research,a sequential adjustment formula is executed with unchanged parameters,however,the parameters usually change during the observation process;meaning that a sequential adjustment formula with unchanged parameters is unsuitable for Network RTK. In addition,old observation measurements are not stored during the sequential adjustment process,thus it is hard to update the normal equation after the ambiguides are fixed. To solve these two problems we use a sequential adjustment formula as well as a rigorous derivation process with changed parameters. Moreover,the update algorithm for the normal equation where ambiguities are fixed is proposed. Experiments with base station ambiguity resolution in long-range network RTK showed that the proposed sequential adjustment formula and update algorithm for the normal equation proposed are appropriate.